alt Hacker NewsUnfortunately, this is one of those HN submissions where people are just knee-jerking to the title without even checking what the submission is. Of course, it doesn't help that it's a long video conference presentation with a "handout" that's beautiful but a little hard to read through on its own.
However, for those that are actually curious, the submission is not itself a cynical or dismissive take. The question in the title is interrogative and contextual, not rhetorical and universal, and the presentation tries to break down some of the bottlenecks and challenges that are leading to AI integration having a different impact on software engineering output than some people might expect.
Rather than suggesting those bottlenecks/challenges are universal or intractable, it just enumerates some of them and presents some survey analyses on how widely encountered they are.
It's actually pretty interesting and the kind of thing that engineers and those who work with them want to be reflecting on, so that they can better engineer their usage and processes around AI itself.
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Let's swap in the subtitle instead. It's blander, so it might be harder to react reflexively* to.
(* https://hn.algolia.com/?dateRange=all&page=0&prefix=true&sor...)
Thanks for the comment. As the author (but I didn't submit it to HN) I see in hindsight that the title should have been a little more informative rather than feeling so click-bait-ey.
My goal was not to imply that we're not shipping faster than we were prior to AI, as I think that's beyond debate at this point. What we investigated is why we're not shipping faster than we are today. If (high quality) code is being written at five times the rate it was before and we're shipping "only" twice as fast, then what's the reason for the difference? The talk shares results from studies that help improve our understanding of why.